An Unified Behaviour Model to Predict Web 2.0

Adoption as a Tool for Software-Knowledge Sharing

Manuel Fernández-Utrilla, Pilar Fernández-Utrilla and Gonzalo Mariscal

Centre of Excellence of Research, Universidad Europea, Spain

Abstract. The most powerful tool for software developers to connect with

each others is social networking. These applications are normally free of

charge. The professional use of these applications exceeds beyond the fun. An

unified behaviour model to predict web 2.0 adoption as a tool for Software-

Knowledge sharing based on two solid and tested theories, theory of planned

behaviour and self-determination theory, will be reached by this study. A

single model, which will join these theories, will accurately predict a use of

these communication tools to set connections among professional groups:

software developers in particular. These models determine the factors that

mainly affect the intention to use described in order to improve these tools with

a high probability of success. These professionals could share knowledge, keys

and bugs in order to find the best solution. A representative number of

software developers have participated in this study in order to research what

the reason is because these professionals do not use these tools with that aim.

Keywords. Knowledge sharing, Social Applications, Theory of planned

behaviour, Self-determination theory, Prediction Model.

1 Introduction

The resolution of bugs or the clarification of specifications, should have found a

great ally in social applications when no solutions is reached. Web 2.0 technologies

(wikis, blogs, social applications, etc.) are playing an ever more important role in the

transfer of information and the reality which is the fact that sharing experiences helps

to improve results. According to the report of the “Observatorio Nacional de las

Telecomunicaciones y los Sistemas de Información [ONTSI]”, “Servicios Utilizados

por los Usuarios de Internet"[1], 52.4% of the users of the network of networks use

social networking technology as Forums, Facebook or Linked-In, a fact which warns

that a large number of professionals will make use of them. There are also reference

studies which show that social applications provide new ways for people to

collaborate, interact, communicate, co-create, and share ideas and knowledge [2].

Authors like Conole and McAndrew [3], confirmed through his published research

based computer tools 2.0 technologies that provide the perfect environment for

learning from communication and the act of sharing real cases every day. Another

important reference of how the exchange of information and experience can help to

find solutions is to Orehovacki, Bubas, and Konecki [4].

Fernández-Utrilla M., Fernández-Utrilla P. and Mariscal G..

An Uniﬁed Behaviour Model to Predict Web 2.0 Adoption as a Tool for Software-Knowledge Sharing.

DOI: 10.5220/0005165900030018

In Proceedings of the 5th International Workshop on Software Knowledge (SKY-2014), pages 3-18

ISBN: 978-989-758-051-2

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

On the other hand and regardless of the fact that the current generation of

software developers available to a high level in the use of social applications, the

professional use is the common denominator of all labor collectives. There are some,

such as university professors, who despite having knowledge are unwilling to use

technology in their classes 2.0 [5]. Through the study, it will be showed what the

intention to use is [6] of certain applications called social networks by software

developers in their daily professional activities.

The software developers’ community has its own professional development

culture [39]with its own problems of cooperation. This study will describe what

factors are necessary to work on in order to reduce the impact of those problems

through a behaviour model. The relationship among main stakeholders is essential

for a successful software development. Cooperation through any mean of

communication is the key to improve the results. It is common that these

professionals publish algorithms and piece of code to share knowledge with other

developers, but several problems such guaratees or supports go with them as well.

Hence software developers’ cooperation follows one sense in most of cases, a

developer shares his consolidate knowledge.

Thorugh this research work, factors which help to develop the cooperation on the

other sense, will be develop. The main goal will be to achieve those software

developers can use social applications to share knowledge and ask for solutions in

order to improve the efficacy of developments. Results will explain how to fight

against these barriers which appear around sharing knowledge through social

applications.

These Internet applications already have a strong position after many years of

operation. Their study began following the theory of six degrees of separation,

whereby it is possible to contact anyone on the planet through six contacts related

among them. The Hungarian writer Frigyes Karinthy proposed this theory in 1929.

The concept is based on the exponential growth of the number of known that each

individual has. Several studies and experiments have been done since this moment to

prove the so-called "six degrees of separation". The best known: Ithiel de Sola Pool

(MIT) and Manfred Kochen (IBM) in 50s and Stanley Milgram in the next decade.

After all, social contacts were uniquely defined as the largest network of existing

information.

The first social networking application set in the mid-90s with the site

www.classmates.com. Randy Conrads created it in 1995. He contacted former

classmates through this site. Subsequently and after the ".COM" crisis began to

appear other websites that they contacted people and creating communities such as

MySpace, created by Microsoft in 2003, or created by Lars Hinrichs Xing in 2003.

These applications are more closely known today as social networks, whether for

leisure or professional use. Currently these tools connect millions of people. A clear

example of these is Facebook, which has over 900 million users worldwide according

to its last report in 2012.

The technology of communication offers a multitude of possibilities through

these social networks. Its main focus is on transfer data from one subject to a

community associated with it [7]. For this is made available to the user several tools

are available for the users in order to develop utilities such as sending private or

public messages, pictures, data, etc. Through all these utilities you can share, discuss,

claim and even create streams of thought. There are different groups in this area that

could use information to improve their performances in relation to the resolution of

critical issues.

However the most powerful tool at present for the transfer of information

between people is not used in the professional field rather than a small percentage of

subjects according to the Observatory of Social Networks in Spain in 2012. It is

difficult to make a scientific explanation. This investigation will determine a

scientific model to predict the use of social networks as a communication tool

between software developers in order to share information and experiences,

improving their results.

2 State of the Art

Social psychology is presented as an option that offers the possibility to intervene in

the conduct of the professional group on which the research is developing: software

developers.

2.1 Theory of Planned Behaviour [TPB]

Theory of Planned Behaviour (TPB) is one of the most proven and accepted theories

in the scientific world. This theory was initially proposed by Professor Icek Ajzen in

1991 and has been subsequently modified and updated in 2006.

The main reason for the use of this theory is the rigorous analysis of all the

factors that make up the execution of the behaviour performed. Each analyzed

behaviour can be evaluated from different angles and therefore be caused by different

sources, but there is a common factor to all of them which is the frequency with

which they occur. The main target of this kind of theory is to discover what the

possibilities of increasing the frequency are by changing its historical causes.

Following the mentioned theory, it should be noted that human behaviour occurs

according to:

• Attitude: software developers can positively or negatively evaluate the use of

social media in their job. The degree in which they are involved, will determine

whether they do have attitude to do or not. They may consider such use helps them

improve their service through shared knowledge or bugs thrown the collective.

• Subjective Norm: is determined by the perceived social pressure on an

individual to perform certain behaviour. In this study, the focus is on the use of social

networking as an effective tool for software developers. The different players around

the subject can influence described pressure: superior, colleagues, family and the

media even.

• Perceived Control: this parameter is directly related to the perception that

software developers have about the possibility of using these social applications in

their daily work, which is running the conduct mentioned. Being specific, these

professionals have Internet access and a multitude of such tools through it. In

addition to their availability, they have the required knowledge to exploit them,

permits and authorizations and the most important: the desire to do it.

These three factors will influence the decision-making intention of professionals

when using social media to improve their daily activity. Therefore, the intention to

use is influenced by attitude, the subjective norm and the perceived control described

above it. The importance of each factor will be different for each worker, as they

present their personal characteristics and potentially different environment.

The intention to perform an activity, action or behaviour, is the precedent

immediately prior to its execution. It can be said since what it has exposed previously

that the particular behaviour can be explained as measurable response that results

from a particular situation in order to achieve a target.

It will need to take a sample large enough to accumulate sufficient number of

observations that allow us to evaluate the behaviour at different times and contexts.

This will generate a greater measurement and more accurate conclusions. In this

investigation, the software developer motivation to use collaborative tools exposed,

will only drive to use them when perceived control is strong enough. That is,

perceived control over the activity in question moderates the effect of intention to

use.

Theory of Planned Behaviour states that behaviour is a variable whose magnitude

will be determined by the combination of intentions and intuition that subjects have

about their control. Professionals who are under this study used social applications, if

and only if, their motivation is right and if they understand how to use.

2.2 Self-Determination Theory [SDT]

Self-Determination Theory is a theory of human motivation that has been widely

used in the health domain. It has been proven in various fields such as sports or

endocrinology [17].

This theory defines two types of behavioural regulation. Firstly, intrinsic

motivation refers to engaging in behaviour of interest, enjoyment or satisfaction

inherent in this behaviour. Secondly and equally important, extrinsic motivation

describes the participation in behaviour for reasons unrelated to their own behaviour

such as social approval.

Making a further development, intrinsic motivation represents the prototype of

autonomous or self-determined motivation according to studies presented by Ryan &

Deci [10]. This motivation is associated with the quality and the persistence of

behaviour. On the opposite side, extrinsic forms of regulation are associated with a

lack of sustained performance over time (and Decision Ryan, 10). In addition, Self-

Determination Theory (SDT) also identifies four types of extrinsic motivation, placed

at various intermediate points along a continuum from intrinsic to extrinsic

motivation. The constant is known as the perceived locus of causality (PLOC).

Self-Determination Theory (SDT) has a significant practical value, in fact, this

theory has been shown to increase behavioural persistence in different studies [12].

However, the SDT predicts that individuals, showing an extrinsic motivation or

controlled, are less willing to show a behavioural persistence.

Recent publications have suggested that autonomous and controlled motivations

or reasons for engaging in behaviour should be different of a person pursue goals

[14]. Other models such as the self-concordance [15] predict that individuals can

pursue goals that are self-consistent or independent, or self and non-self-discordant.

Sheldon and Elliot showed that individuals experience greater progress toward self or

consistent as far as behavioural goals are concerned, as it exerts more effort in your

search. Thus increasing the intention to use specific behaviour should be

accompanied by a fomentation of behavioural persistence.

3 Research Framework

3.1 Integration of Both Theories

In this study, we used behavioural regulation to support her persistence and

predicting the intention of use described in the Theory of Planned Behaviour. The

combination of both theories provides a more accurate prediction of the intention of

performing the behaviour. This improvement will show in the results section where

separating numbers of each theory support this statement.

Theory of Planned Behaviour (TPB) identifies the factors that address the

behaviour but does not explain why individuals create the attitudes, subjective norms

or intentions of use. By contrast, the Self-Determination Theory (SDT) helps explain

these general grounds and contextualizes the social cognitive constructs of the TPB

[16]. A more accurate model for the prediction of intention of execution of behaviour

with the integration of both theories is obtained. There is recent meta-analysis on

studies that integrate both theories providing complementary value between them

[18].

The research framework is defined uniquely by its components: software

developers and tools with an insufficiently exploited commercial potential: social

applications. The aim of the process is the prediction of intention to use social

applications as a software-knowledge sharing tool in a professional setting. This will

be used by software developers to share knowledge and bugs in order to improve

their professional productivity performed daily.

Fig. 1. Contribution – Developed Behaviour Model to Predict.

The developed research framework in this study, our contribution, can be seen on

Figure 1. Through this model, the objective described above can be evaluated. This

intention to use is the result of elements such as attitude, perceived behavioural

control and subjective norm as shown in Ajzen model comprising the Theory of

Planned Behaviour focused on the perception feeling. But this research has expanded

the research framework of the study in order to increase the accuracy of prediction

including another feeling: motivation. In particular two types of motivation,

autonomous and controlled derived from the Self-Determination Theory whose

development began with the studies of Decision in 1970. Note that all constructs

selected for study were chosen, validated and published in high impact research.

This framework works on the following assumptions:

• H1-H2: The self-managed privacy of the professional concerned is a factor that

negatively affects the intention to use since seeing their exposure on a social network

as a potential violation of privacy of the software developments. They can also see

that this potential invasion of privacy of the software developments affects their

effective use of social applications for the purpose.

• H3-H4: The development privacy, to which these professionals help, is also a

factor that negatively affects the intention to use since seeing this exhibition in a

social application as a potential violation of the privacy of the software

developments. They may also perceive that this potential intrusion into the privacy of

their organizations will affect current use of social applications for the purpose.

• H5: Ease of use of applications that allow managing social applications, positively

influence the software developers’ attitude towards the use of social networks.

• H6: Interactivity that may exist among colleagues through these systems, results in

a considerable improvement in the attitude they have software developers towards

the use of social applications.

• H7: The usefulness of these telematics programs have to improve the outcomes of

their developments. It will be positively assessed by software developers towards the

use of social applications.

• H8: The compatibility with the infrastructure that developers must use to work. It

will be positively assessed by professional software developers towards the use of

social applications.

• H9: Perceived self-efficacy, related to the choice to improve their daily work, will

be highly valued in perceived behavioural control they undergo this professional

sector. That is why a positive degree of autonomy is presented as essential to have

the expected results.

• H10-H15: It will be based on the assumption that elements such as attitude, both

autonomous and controlled motivation, normative beliefs and perceived behavioural

control will have a positive effect on the intention to use social applications from this

professional group.

3.2 Research Metodology

Data collection method used was to send questionnaires and receive the

corresponding data from their responses. The research consisted of four main phases:

research framework development, construction and validation of the questionnaire,

data collection and finally, data analysis.

3.2.1 Construction and Validation of Questionnaire

The first part of the questionnaire will obtain demographic information about gender,

age, social application usage, specific application used, etc... The rest of the

questions that take part in the developed tool have been selected from studies with

validated and adapted questionnaires to the context of the current study. In addition,

the questionnaire was piloted to confirm its validity and reliability. All survey

questions were scored on a scale "Likert" of 5 points ranging from the "1" that

expresses complete disagreement, to the "5" represents the entire agreement. In the

questionnaire are uniquely intermediate points in order to avoid mistakes.

Moreover, despite having built the questionnaire with questions from validated

questionnaires [19], there has been a pilot from 102 users to contrast reaching valid

correlation values necessary to be eligible for the study.

Related to selected questions, these are chosen from a study written in a different

language than the language in which this research has been developed. It has made

use of the normalized inverse translation process as it is one of the most suitable for

problems associated with poor translations or adaptations, and thus, to evaluate the

quality of translation [20, 21].

3.2.2 Data Collection

We have developed a questionnaire on a online tool in order to make easy the full

filling of questionnaires by software developers. This can be distributed easily,

quickly and economically among the largest number of software developers who

have been contacted by the software factories to which we made contact with. The

number of responses was 328 of which have had to remove 26 by various errors. The

table 1 shows the profile of the people who responded to the survey sent:

Table 1. Demographics.

18 < years <=

18,20%

26 < years <=

38,74%

36 < years <=

27,45%

Years > 45 15,61%

Female 15,31%

Male 84,69%

Degree 75,57%

Master 19,15%

Doctorate 5,28%

Forum 92,56%

Facebook 21,20%

Linked-In 9,21%

Age

Gender

Edu c a t i o n

Social Network Use

3.2.3 Data Analysis

We used structured equation modeling (SEM) to examine the relationships among

constructs selected. Several methods could be used but its flexibility and generality

are its strong points. SEM has rapid developments and expansion. It has been chosen

the least squares regression method for their ability to work with small sample sizes.

This is the reason because most of behaviour model studies in which it is difficult to

get large samples, use SEM in order to show more accurate results. SEM takes a

confirmatory (hypothesis testing) approach to the multivariate analysis of a structural

theory, one that stipulates causal relations among multiple variables [41].

SmartPLS 2.0.M3 [22] was used for measurements on research hypotheses

described above. Chin [23] shows in their studies to obtain meaningful

interpretations, the relational coefficient values must be above 0.2. This method

provides two components of a causal model: measurement and structured model.

Furthermore, it is particularly suitable for research with significant variances.

3.2.4 Reliability and Validity

Firstly, separated results of each theory related to the parameter R2 will show the

improvement that the research has undergone [38]. The same goal, the intention to

use of a particular behaviour, through two different psychological factors: perception

(TPB) and motivation (SDT). The last three columns show the results through the

research model.

The following table shows how the research model improves the results exposed

in this paper. This fact can be inferred since the coefficient of determination (R

) of

the different models. This statistical element is used in trend analysis. It is computed

as a value between 0 (0 percent) and 1 (100 percent). The higher the value, the better

the fit. TPB and SDT theories offer a R

factor below the same element in the

research model. Following the mean of this statistic parameter, the research model is

more solid than the other theories applied by separated.

In addition, load factors, the average composite reliability and the obtained mean

have been showed in order to expose the full research statistics. Load factors must be

at least 0.6 and preferably greater than 0.7 [23]. Almost all factor loadings exceeding

these thresholds. The “t” statistic, obtained by bootstrapping (200 resamples) showed

that all factor loadings are significant at the 0.001 level. Observed reliability of

constructs (compound reliability) for each construct (see Table 2) is greater than 0.8

(Fornell and Lacker 1981). All loadings were significant constructs above the

recommended value of “p“ of 0.05 (Gefen and Straub 2005) and have generally

exceeded the recommended threshold value of 0.707 (Barclay et al. 1995). The

average variance extracted (AVE or Average Variance Extracted) was above the

minimum of 50 percent of the variance for each construct and the square root of the

AVE for each construct was much higher than the correlation of the construct with

each other construct (Barclay et al 1995. Gefen and Straub 2005).

The means of the loaded items in each respective construct gives a value of at

least 0.1 greater than the load in other constructs (Barclay et al, 1995; Gefen and

Straub 2005) and all the items loaded is greater than the expected construct any other

construct. Therefore, it can be concluded that measured constructs were consistent

and showed a substantial degree of convergence and discriminating validity.

Table 2. Improvement through the research model.

Theory Construct

Theory of

Planned

Behaviour

(TPB)

Attitude 0,291

Perceived

Control

Behaviour

0,254

Normative

Belief s

0,243

Intention to

Us e

0,296

S. Netw ork

Us e

0,312

Theory Construct

Self-

Determ inatio

n Theory

(SDT)

Self-Motivation 0,218

Controlled

Mot iv at ion

0,263

Intention to

Us e

0,278

S. Netw ork

Us e

0,292

Theory Construct

Research

Model

Attitude 0,469

Perceived

Control

Behaviour

0,401

Normative

Belief s

0,381

Self-Motivation 0,343

Controlled

Mot iv at ion

0,397

Intention to

Us e

0,398

S. Netw ork

Us e

0,453

Table 3. Reliability and Validity of the Research Framework.

Table 4. Social Applications Knowledge Level.

Conclusions

Regarding the knowledge level about social applications, this research has been able

to get a picture of what different highlighted aspects are. In addition, it is important

to know which social application is necessary to work in the study. The obtained

results are summarized in the table below (n = 302):

A forum is the social application that achieves a higher knowledge level under

study:

Factor Ítem Load Statistical t AVE Cronbach

Composite

reliability

PRIVP1 0.764 14.287

PRIVP2 0.783 22.342

PRIVP3 0.812 13.223

PRIVPC1 0,804 19.332

PRIVU1 0.877 14.112

PRIVU2 0.721 27.332

PRIVU3 0.833 11.575

PRIVUC1 0,725 21.221

USA1 0.809 13.115

USA2 0.912 33.556

Interactivity

INTERACT1 0,908 11,998 1.000 1.000 1.000 -

UTI1 0.808 12.118

UTI2 0.811 23.429

UTI3 0.789 11.398

UTI4 0,743 22.344

COMP1 0.834 55.332

COMP2 0.853 39.223

COMP3 0.812 51.332

COMP4 0.765 50.332

COMP5 0.811 39.338

AUT1 0.811 2.221

AUT2 0.901 3.119

ACT 1 0.723 15.992

ACT 2 0.790 24.323

ACT 3 0.784 33.221

ACT 4 0.811 29.332

ACT 5 0.734 25.122

CNCS1 0.832 5.223

CNCS2 0.822 7.011

CNCS3 0.789 7.232

CNMED1 0.897 18.213

CNMED2 0.899 26.887

CCP1 0.709 9.012

CCP2 0.787 10.998

MOTA1 0.810 78.998

MOTA2 0.843 79.011

MOTC1 0.710 81.011

MOTC2 0.878 80.110

Intended use

IU1 1 6.982 0.781 0.711 0.810 0,398

Use of social

appl icati ons

USARED1 1 7.891 0.801 0.809 0.819 0,453

Self

Motivation

0.801 0.865 0.891 0,343

Controlled

motivation

0,71 0,707 0,832 0,397

Media

0,845 0,823 0,854 0,332

Perceived

control

conditions

0.801 0,775 0,732 0,413

Attitude

0.743 0,789 0,712 0,469

Social context

0,721 0,799 0,798 0,381

Compatibility

0.722 0,798 0.811 -

Self-efficacy

0.789 0,721 0.899 -

Usability

0.719 0,717 0,842 -

Utility

0.764 0.789 0,855 -

0.783 0,814 -

Th i rd P a r t

Protection

0.711 0.732 0,811 -

Self Privacy

0.732

Social

Application

Forums Facebook Linked‐In

NeverUsed 3,97% 11,26% 18,54%

Beginner 8,28% 22,52% 40,73%

Competent 67,22% 54,97% 32,12%

Expert 20,53% 11,26% 8,61%

Knowledge

Level

Fig. 2. Individual results about social applications knowledge level.

Main conclusions are divided between variables which have a positive impact in

the intention of use and the variables which have a negative impact. Firstly, since test

results show that all variables of Theory of Planned Behaviour and Self-

Determination Theory: attitude, subjective norm and perceived control, provide an

important and significant component of the intention to conduct and perform in

herself from certain behaviour. On the one hand the feeling of "perception" is

remarkable, being motivation as a clearly secondary sense. Safety is presented as the

main element in the aspects that have a negative contribution; in this case the zeal in

the personal data is very important balancing equal parts: fear of job loss against

potential negligence, and fear the potential violation of private data, themselves or

others, arranged in the network.

By contrast, elements such as usability, usefulness or self-efficiency, enhance

the use of social applications in order to be a tool for sharing knowledge improving

software developments. As important conclusions and issues to work are taken from

the following key points of the research on the software developers (in order of

appearance on the issues referenced in the survey):

 Forum is the most used social application.

 Social developers have a weak knowledge of safety policies and have been

rarely configured. Only 50% people under study report having ever done. This

is the first aspect to improve. To mitigate this aspect, it is proposed to set up

training programs in order to show possibilities which security levels in these

kinds of applications can offer. Myths and misunderstandings will be eliminate

in many cases and will definitely help them.

 The self-privacy of software developers is an issue that stops the use of social

applications for any professional aspect. A large majority of workers refuses to

use them because they do not control what is done with the information that

there is in this kind of applications. This, after analyzing the full study, has a

negative effect on the attitude towards the use and perceived behavioural

control, which also directly impact on the intention to perform the behaviour.

The main highlighted factor in the interviews has been the lack of knowledge

about these technical issues: configuration and knowledge of data treatment.

Two initiatives are proposed to mitigate this issue. The first one is to share

between users and service provider. The second one is to start the training way

in order to fill knowledge gaps.

0,00%

20,00%

40,00%

60,00%

80,00%

NeverUsed

Beginner

Competent

Expert

 In the service provider case, two main tasks are proposed: firstly clarify the

security interfaces with illustrative examples of what can be done and what not

from activation or cancellation of each of the security sections. Secondly, it is

proposed the creation of default configuration profiles for professional activities

that help their activation and use. This would provide a value that can be

quantified in confidence created in the link that connects the user to the

provider via the application.

 The protection of security linked to the security of user data on which an

intervention is developed is critical. Two important aspects are concentrated

around this point. On the one hand the potential violation of user data, not

software developer personal data, without knowing the use that service provider

will be given. Furthermore, the possible negligence that could commit to make

public although the purpose of such disclosure is proactive in looking for a

solution that help user interests.

 To mitigate both points raises the following proposals. Firstly, users would be

informed how to work in order to be aware of and rate the effort required and

especially the rise of human resources in the service of the resolution of their

case. Secondly, it would create a text to be signed by users seeking help through

which the practitioner is exempt from any liability acquired and got eliminating

susceptibility by professionals towards this issue.

 The construct related to the "Usability" positive impacts on the attitude to use a

social application as a tool. Such systems, in particular forums, have permeated

public common knowledge so much that its use has become common

knowledge. Therefore a large majority of the population in general, and

certainly a majority representative of the group involved in the study, expressed

his comfort towards the use of these tools through Internet. The front ends,

performed considering some usability rules, have become commonplace.

Desings, that are developed based on intuition from the literature, are merely

imitations of interfaces that, due to commercial fashions, have spread among

the population. Therefore if we stick to technical definitions of usability, are

unlikely to be met strictly. Perhaps the correct term to use would be

"familiarity".

 As previously mentioned, this factor positively influences the attitude,

positively influences the intention to perform the behaviour and implementation

of the same by direct action.

 The "Interactivity" factor has no influence on the main elements of the used

theories from the results. Its impact on the attitude toward performing the

behaviour is minimal. The vast majority of the subjects involved in the study

did not consider the interactivity that networks provide is to be decisive in their

use.

 To mitigate this effect and ensure that this factor is an incentive to increase the

intention to use, we propose show real examples to software developers the

benefit of interactivity among professionals. To show habitual patterns and

typical cases in which they see themselves in their daily activity helping to

verify that this is a valid solution to improve performance. Such interactivity as

technological element is something that is passed. The solutions allow a high

degree of interaction among humans in order to share any type of knowledge,

while avoiding the need to be in the same location.

 All these advantages should be shown to the professionals in order to put in

relevance the access to delocalized knowledge, in this case, focusing on the

experience of other professionals who would be available to other people.

 According to the initial hypothesis, the construct that should have a more

important and positive impact on the other elements of the research model, is

"Utility" without any doubt. Since results show, the utility is a concept that has

been embraced by software developers. More than 66% are aware and agree

with social applications as support for improving the results of its operations.

Therefore the attitude to use is positive and a first component of our initial

hypothesis is confirmed. Professionals see a lot of advantages.

 In this research, the problem presented is how to implement this assistance

proposed to them. That is, although they see many advantages and benefits in

the use of these applications, when they are proposed to include them in their

daily routine tasks, answers are negative or neutral. Therefore, in the full model

analysis and taking into account all contributions, we must make a distinction

that justifies the neutral contribution to this construct. The sum of these two

components, theoretical and practical utility, is neutral, offsetting the resulting

weights of responses on both points of view.

 Since the results of the survey, the construct "Compatibility" has not

contribution in the attitude to perform the behaviour. The group of software

developers do not consider neither positive nor negative. Most of them perceive

it from the indifference. This factor has been measured mainly about their daily

tasks. Professionals have not considered as a relevant one and that is the reason

because the indicators have pointed out that it is not a factor that significantly

influences the attitude. Therefore it has not impact in the intention to use.

 As action to mitigate this perception, again training programmes are proposed.

The use of nowadays cases and simple examples help them to undertand. The

cases should show sectors or occupations where the use of such applications

could provide significant added value, and due to compatibility reasons with

their profession, their implementation is not possible.

 "Auto-Efficiency" shows that software developers perceive that they have the

knowledge necessary to use and enjoy the benefits that these tools proposed in

their professional duties. His contribution to perceived behavioural control

element is positive and this can be seen in the increase of the intention to use.

Finally we present the motivation analysis in the full research model to predict the

intention to use. For this professional group, motivations have not a positive impact

to the intention to perform behaviour. This fact contradicts the research hypothesis in

which software developers are supposed to find the possibility of improving their

work as an incentive to use such online tools.

 Firstly self-motivation does not exist. Hence, the lack of impact on the intention

to perform the behaviour. To mitigate this element of the model, it should work

on motivating staff through professional development in order to improve their

professional competences. The skill development is a common strategy used by

human resources departments in large companies. Among several competences,

the use of new technologies to improve professional performance should be the

goal to mitigate the absence of autonomous motivation in this group.

 Secondly controlled motivation is presented. As previously mentioned, this

motivation is based on making demands from the top of the organization. In this

aspect, user survey shows that this professional group is against any kind of this

motivation. Therefore this factor will have a negative impact. The frequency of

performing the behaviour will not rise.

In terms of mitigation of this aspect, an imposition of a superior must be seen as

a risk or a threat of being fired. From this start point, the intention to use will be

clearly identified positively.

5 Considerations and Future Research

The main considerations to take into account in this research are: firstly, software

developers group is an important professional group that has a manifest disregard of

the safety aspects of these applications can provide them. Being a technical field far

away from his common one, being a new technology related to internet and where

they have committed many crimes on the violation of privacies, all this makes the

intention of use of social applications by software developers in order to improve

their productivity is weak.

Therefore, it is too complicated to share high-level software knowledge among

them. In these cases, it is obvious that the first step would be to provide them the

right knowledge from a professional trainer to enable them to become confident

enough to develop their work with guarantees and also improve their performance

through shared knowledge.

Next steps in this research will be to work with other professional groups who

share the characteristic of work directly related to groups of people. The teacher staff

of one university is the next start point to research and contrast this predict model. In

this case we will work on prediction models about behaviours related to the use of

social networks to share information and experiences in order to improve the

relationship with the student, their evaluations, tests, etc.

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